Granularity issues in the alignment of upper ontologies.

OBJECTIVES: The application of upper ontologies has been repeatedly advocated for to support the interoperability between different domain ontologies for facilitating the shared use of data within and across disciplines. BioTop is an upper domain ontology that aims at aligning more specialized biomolecular and biomedical ontologies. The integration of BioTop and the upper ontology Basic Formal Ontology (BFO) is the objective of this study. METHODS: BFO was manually integrated into BioTop, observing both its free text and formal definitions. BioTop classes were attached to BFO classes as children and BFO classes were reused in the formal definitions of BioTop classes. A description logics reasoner was used to check the logical consistency of this integration. The domain adequacy was checked manually by domain experts. RESULTS: Logical inconsistencies were found by the reasoner when applying the BFO classes for fiat and aggregated objects in some of the BioTop class definitions. We discovered that the definition of those particular classes in BFO was dependent on the notion of physical connectedness. Hence we suggest ignoring a BFO subbranch in order not to hinder cross-granularity integration. CONCLUSION: Without introducing a more sophisticated theory of granularity, the described problems cannot be properly dealt with. Whereas we argue that an upper ontology should be granularity-independent, we illustrate how granularity-dependent domain ontologies can still be embedded into the framework of BioTop in combination with BFO.

Modeling functional neuroanatomy for an anatomy information system.

OBJECTIVE: Existing neuroanatomical ontologies, databases and information systems, such as the Foundational Model of Anatomy (FMA), represent outgoing connections from brain structures, but cannot represent the "internal wiring" of structures and as such, cannot distinguish between different independent connections from the same structure. Thus, a fundamental aspect of Neuroanatomy, the functional pathways and functional systems of the brain such as the pupillary light reflex system, is not adequately represented. This article identifies underlying anatomical objects which are the source of independent connections (collections of neurons) and uses these as basic building blocks to construct a model of functional neuroanatomy and its functional pathways. DESIGN: The basic representational elements of the model are unnamed groups of neurons or groups of neuron segments. These groups, their relations to each other, and the relations to the objects of macroscopic anatomy are defined. The resulting model can be incorporated into the FMA. MEASUREMENTS: The capabilities of the presented model are compared to the FMA and the Brain Architecture Management System (BAMS). RESULTS: Internal wiring as well as functional pathways can correctly be represented and tracked. CONCLUSION: This model bridges the gap between representations of single neurons and their parts on the one hand and representations of spatial brain structures and areas on the other hand. It is capable of drawing correct inferences on pathways in a nervous system. The object and relation definitions are related to the Open Biomedical Ontology effort and its relation ontology, so that this model can be further developed into an ontology of neuronal functional systems.